Search Results (15,141)

Background/Objectives: Classical swine fever (CSF) continues to challenge global eradication efforts, particularly in endemic regions, where pregnant sows face heightened risks of vertical transmission following exposure to CSFV. Methods: This study evaluates the early protective efficacy of FlagT4G, a novel live attenuated DIVA-compatible vaccine. Pregnant sows were vaccinated at mid-gestation and challenged 14 days later with a highly virulent CSFV strain. Results: FlagT4G conferred complete clinical protection, preventing both maternal viremia and transplacental transmission. No CSFV RNA, specific antibodies, or IFN-α were detected in fetal samples from vaccinated animals. In contrast, unvaccinated sows exhibited clinical signs, high viral loads, and widespread fetal infection. Interestingly, early protection was observed even in the absence of strong humoral responses in some vaccinated sows, suggesting a potential role for innate or T-cell-mediated immunity in conferring rapid protection. Conclusions: The demonstrated efficacy of FlagT4G within two weeks of vaccination underscores its feasibility for integration into emergency vaccination programs. Its DIVA compatibility and ability to induce early fetal protection against highly virulent CSFV strains position it as a promising tool for CSF control and eradication strategies. Full article

Accelerated urbanization and intensified urban development globally lead to increased sewage discharge, challenging environmental protection. Therefore, exploring the correlation mechanism between the economic development level (EDL) and sewage discharge intensity (SDI) is crucial for sustainable development. This study uses panel data from 288 Chinese cities between 2003 and 2021, employs spatial analysis techniques to uncover the spatiotemporal evolution characteristics of SDI, and investigates the influence of economic development on this intensity using spatial panel models. The results reveal that (1) while the spatial distribution of SDI in China generally exhibits a downward trend, changes in the Northeast region are relatively modest, with SDI remaining higher than in other regions. Global autocorrelation analysis further indicates significant spatial agglomeration and positive correlation effects in urban SDI. (2) Economic development exerts a notable inhibitory effect on SDI, with a 0.570% decrease for every 1% rise in GDP per capita, thus demonstrating a significant spatial spillover effect. (3) For megacities, large cities, and small and medium-sized cities, EDLs have significant negative spatial spillover effects on SDI, with a more pronounced impact on large cities. This study provides a theoretical foundation for sewage management and empirical support for environmental policies, crucial for sustainable urban development. Full article

Background: Soccer is a physically demanding sport characterized by frequent high-intensity efforts, which are particularly relevant in women’s competitions. Improving high-speed running and aerobic capacity has been linked to better on-field performance. Strength training has shown promise in enhancing these physical attributes, but its application in young female soccer players remains underexplored. This study aimed to investigate the effects of a 10-week in-season strength training program on physical performance and match running demands in young female soccer players. Methods: Thirty-two U18 Danish female professional soccer players from two comparable teams voluntarily participated in the study. Teams were allocated to either an experimental group, performing twice-weekly strength training (EG, n = 16) or a control group (CG, n = 16). Vertical jump performance and Yo-Yo IR2 performance as an estimation for maximal oxygen uptake (VO₂max) were assessed both pre and post intervention. Additionally, players’ match external demands (i.e., total distance, distance covered at speeds above 23 km·h⁻¹, and maximum velocity achieved) were monitored using Global Positioning System devices during four matches before and after the intervention. Results: Significant within-group differences were observed across all variables for the EG (p = 0.001; ES = 1.08 to 1.45, large), without differences in the CG (p > 0.01). Between-group analysis indicated significant differences favoring the EG in all variables (F = 27.40 to 47.17; p = 0.001). Conclusions: The application of a 10-week strength training program led to improvements in physical and match running performance among young female soccer players, underscoring the importance of incorporating strength training programs into female soccer periodization to enhance performance. Full article

Designing optimal heritage tourism routes in secondary cities involves complex trade-offs between cultural richness, travel time, carbon emissions, spatial coherence, and group satisfaction. This study addresses the Personalized Group Trip Design Problem (PGTDP) under real-world constraints by proposing DRL–IMVO–GAN—a hybrid multi-objective optimization framework that integrates Deep Reinforcement Learning (DRL) for policy-guided initialization, an Improved Multiverse Optimizer (IMVO) for global search, and a Generative Adversarial Network (GAN) for local refinement and solution diversity. The model operates within a digital twin of Warin Chamrap’s old town, leveraging 92 POIs, congestion heatmaps, and behaviorally clustered tourist profiles. The proposed method was benchmarked against seven state-of-the-art techniques, including PSO + DRL, Genetic Algorithm with Multi-Neighborhood Search (Genetic + MNS), Dual-ACO, ALNS-ASP, and others. Results demonstrate that DRL–IMVO–GAN consistently dominates across key metrics. Under equal-objective weighting, it attained the highest heritage score (74.2), shortest travel time (21.3 min), and top satisfaction score (17.5 out of 18), along with the highest hypervolume (0.85) and Pareto Coverage Ratio (0.95). Beyond performance, the framework exhibits strong generalization in zero- and few-shot scenarios, adapting to unseen POIs, modified constraints, and new user profiles without retraining. These findings underscore the method’s robustness, behavioral coherence, and interpretability—positioning it as a scalable, intelligent decision-support tool for sustainable and user-centered cultural tourism planning in secondary cities. Full article

More than 50 years ago, children were viewed as naturally resilient and often labeled invulnerable or invincible. Resilience is now understood to be the result of dynamic interactions between individual, familial, social, and environmental systems, decentralizing the focus from the individual to the global society. Experiences with adversity may emanate from the youth’s family environment, their community, the school system, and larger structural challenges related to poverty, discrimination, health disparities, and educational inequities. Youth experiences with adversity, trauma, and tragedy have the potential to negatively impact youth well-being, with consequences manifesting across the lifespan. Children and adolescents generally hold limited power to change their circumstances and are often ill-equipped to resolve the adverse or traumatic experiences occurring within their ecosystem. The value of social supports in the young person’s ability to be resilient has been affirmed. This understanding is particularly important for children growing up in poverty or in Low- and Middle-Income Countries (LMICs) where significant challenges occur as a result of economic and social disadvantage. Resilience at the individual level is unlikely to eliminate macrolevel issues. Developing and deploying strategies to enhance the ability of youth to rebound from adversity represents a positive step at the micro level, but the larger issues of economic and social disadvantage are unlikely to change without macro-level interventions. Glancing toward the future, traumatized youth may grow into traumatized adults without appropriate interventions and changes in social policies, programs, and protections. Full article

This paper presents the design of a wideband circularly polarized crossed-dipole antenna for multi-GNSS applications, covering the frequency range of 1.16–1.61 GHz. The proposed antenna employs orthogonally placed dipole elements fed by a three-branch quadrature hybrid coupler for broadband and wide gain/axial ratio beamwidth. The design is carried out using CST Studio Suite for a single dipole antenna followed by a crossed-dipole antenna, a feed network, and the entire antenna structure. The designed multi-GNSS antenna shows, at 1.16–1.61 GHz, a reflection coefficient of less than −17 dB, a zenith gain of 3.9–5.8 dBic, a horizontal gain of −3.3 to −0.2 dBic, a zenith axial ratio of 0.6–1.0 dB, and horizontal axial ratio of 0.4–5.9 dB. The proposed antenna has a dimension of 0.48 × 0.48 × 0.25 λ at the center frequency of 1.39 GHz. The proposed antenna can also operate as an LHCP antenna for L-band satellite phone communication at 1.525–1.661 GHz. Full article

In recent years, a growing number of real-time semantic segmentation networks have been developed to improve segmentation accuracy. However, these advancements often come at the cost of increased computational complexity, which limits their inference efficiency, particularly in scenarios such as autonomous driving, where strict real-time performance is essential. Achieving an effective balance between speed and accuracy has thus become a central challenge in this field. To address this issue, we present a lightweight semantic segmentation model tailored for the perception requirements of autonomous vehicles. The architecture follows an encoder–decoder paradigm, which not only preserves the capability for deep feature extraction but also facilitates multi-scale information integration. The encoder leverages a high-efficiency backbone, while the decoder introduces a dynamic fusion mechanism designed to enhance information interaction between different feature branches. Recognizing the limitations of convolutional networks in modeling long-range dependencies and capturing global semantic context, the model incorporates an attention-based feature extraction component. This is further augmented by positional encoding, enabling better awareness of spatial structures and local details. The dynamic fusion mechanism employs an adaptive weighting strategy, adjusting the contribution of each feature channel to reduce redundancy and improve representation quality. To validate the effectiveness of the proposed network, experiments were conducted on a single RTX 3090 GPU. The Dynamic Real-time Integrated Vision Encoder–Segmenter Network (DriveSegNet) achieved a mean Intersection over Union (mIoU) of 76.9% and an inference speed of 70.5 FPS on the Cityscapes test dataset, 74.6% mIoU and 139.8 FPS on the CamVid test dataset, and 35.8% mIoU with 108.4 FPS on the ADE20K dataset. The experimental results demonstrate that the proposed method achieves an excellent balance between inference speed, segmentation accuracy, and model size. Full article

The world is facing a state of “global boiling,” causing damage to various sectors. Developing pedestrian systems is a key to mitigating it, especially in tropical and humid cities where the climate discourages walking and increases the need for shaded walkways. Recent research shows a lack of data and in-depth studies on the built environment promoting walkability in such climates, creating a research gap this study aims to fill. Using Singapore as a case study, four locations—Marina Bay, Orchard Road, Boat Quay, and Chinatown—were surveyed and analyzed through visual decoding and questionnaires. Results show that natural light is the most frequently observed and important element in pedestrian pathway design in tropical and humid areas. Trees and sidewalks are also important in creating a walk-friendly environment. Green spaces significantly influence the desire to walk, though no clear positive outcomes were found. Additionally, “Other Emotions” negatively affect the decision to walk, suggesting these should be avoided in future pedestrian pathway designs to encourage walking. Full article

Land cover, topography, precipitation, and socio-economic factors exert both direct and indirect influences on urban land surface temperatures. Within the broader context of global climate change, these influences are magnified by the escalating intensity of the urban heat island effect. However, the interplay and underlying mechanisms of natural and socio-economic determinants of land surface temperatures remain inadequately explored, particularly in the context of cold-region cities located in the northern temperate zone of China. This study focuses on Changchun City, employing multispectral remote sensing imagery to derive and spatially map the distribution of land surface temperatures and topographic attributes. Through comprehensive analysis, the research identifies the principal drivers of temperature variations and delineates their seasonal dynamics. The findings indicate that population density, night-time light intensity, land use, GDP (Gross Domestic Product), relief, and elevation exhibit positive correlations with land surface temperature, whereas slope demonstrates a negative correlation. Among natural factors, the correlations of slope, relief, and elevation with land surface temperature are comparatively weak, with determination coefficients (R²) consistently below 0.15. In contrast, socio-economic factors exert a more pronounced influence, ranked as follows: population density (R² = 0.4316) > GDP (R² = 0.2493) > night-time light intensity (R² = 0.1626). The overall hierarchy of the impact of individual factors on the temperature model, from strongest to weakest, is as follows: population, night-time light intensity, land use, GDP, slope, relief, and elevation. In examining Changchun and analogous cold-region cities within the northern temperate zone, the research underscores that socio-economic factors substantially outweigh natural determinants in shaping urban land surface temperatures. Notably, human activities catalyzed by population growth emerge as the most influential factor, profoundly reshaping the urban thermal landscape. These activities not only directly escalate anthropogenic heat emissions, but also alter land cover compositions, thereby undermining natural cooling mechanisms and exacerbating the urban heat island phenomenon. Full article

The global antimicrobial resistance crisis demands innovative strategies to combat bacterial infections, including those caused by drug-sensitive pathogens that evade treatment through biofilm formation or metabolic adaptations. Here, we demonstrate that Squama Manitis extract (SME)—a traditional Chinese medicine component—exhibits broad-spectrum bactericidal activity against clinically significant pathogens, including both Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) species (MIC = 31.25 mg/mL), achieving significant reduction in bacterial viability within 24 h. Through integrated multi-omics analysis combining scanning electron microscopy and RNA sequencing, we reveal SME’s unprecedented tripartite mechanism of action: (1) direct membrane disruption causing cell envelope collapse, (2) metabolic paralysis through coordinated suppression of TCA cycle and fatty acid degradation pathways, and (3) inhibition of DNA repair systems (SOS response and recombination downregulation). Despite its potent activity, SME shows low cytotoxicity toward mammalian cells (>90% viability) and can penetrate Gram-negative outer membranes. These features highlight SME’s potential to address drug-resistant infections through synthetic lethality across stress response, energy metabolism, and DNA integrity pathways. While advocating for synthetic alternatives to endangered animal products, this study establishes SME as a polypharmacological template for resistance-resilient antimicrobial design, demonstrating how traditional knowledge and modern systems biology can converge to guide sustainable anti-infective development. Full article

Nephrolithiasis, predominantly driven by calcium oxalate (CaOx) crystal deposition, poses a significant global health burden due to its high prevalence and recurrence rates and limited preventive/therapeutic options. Recent research has underscored a pivotal role for macrophage polarization in nephrolithiasis pathogenesis. Pro-inflammatory phenotype macrophages exacerbate crystal-induced injury and foster stone formation by amplifying crystal adhesion via an NF-κB–IL-1β positive-feedback axis that sustains ROS generation and NLRP3 inflammasome activation, whereas anti-inflammatory phenotype macrophages facilitate crystal clearance and tissue repair. We have summarized the research on treating nephrolithiasis and related renal injury by targeting macrophage polarization in recent years, including therapeutic approaches through pharmacological methods, epigenetic regulation, and advanced biomaterials. At the same time, we have critically evaluated the novel therapeutic strategies for macrophage reprogramming and explored the future development directions of targeting macrophage reprogramming for nephrolithiasis treatment, such as using single-cell/spatial omics to reveal the heterogeneity of macrophages in the stone microenvironment, chimeric antigen receptor macrophages (CAR-Ms) as a potential therapy for specific crystal phagocytosis in certain areas, and multi-omics integration to address inter-patient immune differences. This review highlights that macrophage reprogramming is a transformative frontier in nephrolithiasis management and underscores the need for further research to translate these molecular insights into effective clinical applications. Full article

The International Maritime Organization (IMO) has set a goal to reach net-zero greenhouse gas emissions from international shipping by or around 2050. The ship energy efficiency framework has played a positive role over the past decade in improving carbon intensity and reducing greenhouse gas emissions by employing the technical and operational energy efficiency metrics as effective appraisal tools. To quantify the ship energy efficiency performance and review the existing energy efficiency framework, this paper analyzed the data for the reporting year of 2023 extracted from the European Union (EU) monitoring, reporting, and verification (MRV) system, and investigated the operational profiles and energy efficiency for the ships calling at EU ports. The results show that the data accumulated in the EU MRV system could provide powerful support for conducting ship energy efficiency appraisals, which could facilitate the formulation of decarbonization policies for global shipping and management decisions for stakeholders. However, data quality, ship operational energy efficiency metrics, and co-existence with the IMO data collection system (DCS) remain issues to be addressed. With the improvement of IMO DCS system and the implementation of IMO Net-Zero Framework, harmonizing the two systems and avoiding duplicated regulation of shipping emissions at the EU and global levels are urgent. Full article

Neisseria gonorrhoeae, the causative agent of gonorrhea, represents a major public health concern due to its increasing antimicrobial resistance. While often asymptomatic—particularly in extragenital infections—untreated cases can lead to severe complications and further transmission. Despite global efforts to monitor antimicrobial resistance, data on the molecular determinants underlying decreased susceptibility in N. gonorrhoeae remain scarce in Peru. This study aimed to detect mutations in the penA and 23S rRNA genes, which confer decreased susceptibility to cephalosporins and azithromycin resistance. We extracted DNA from 124 N. gonorrhoeae-positive clinical rectal specimens collected in Aptima Combo 2 transport tubes from MSM patients. These DNA samples were then screened using the Mismatch Amplification Mutation Assay-based real-time PCR (MAMA-qPCR) to identify mutations in the 23S rRNA and penA genes. Each sample underwent separate reactions to detect A2059G and C2611T mutations in the 23S rRNA gene, and 86 of these samples were further tested in individual qPCR assays for the penA D345 deletion (D345del) or G545S mutations. Sanger sequencing was performed on all DNA samples positive for 23S rRNA mutations by MAMA-qPCR assay, and on 27 DNA samples that yielded sufficient penA amplicons for additional sequencing. Using the MAMA-qPCR assay for the 23S rRNA gene, 64 of 124 samples amplified in the A2059G reaction: 2 (3.1%) carried the mutation, and 62 were classified as wild type. In the C2611T reaction, 42 of 124 samples amplified, and none of them carried the mutation. Using the MAMA-qPCR assay for the penA gene, we only analyzed 86 samples, as the remaining 38 samples had insufficient DNA yield. A total of 44 of the 86 samples amplified in the D345del reaction: 5 (11.4%) carried the D345del, and 39 were classified as wild type. In the G545S reaction, 4 (6.4%) carried the mutation, and 58 were classified as wild type. Finally, sequencing of the penA gene in the 27 samples revealed mutations related to decreased susceptibility to cephalosporins. This study identified genetic mutations conferring resistance to azithromycin and decreased susceptibility to cephalosporins, providing an overview of the circulating mutations conferring resistance in N. gonorrhoeae strains in Peru. Full article

This paper proposes a novel Global Navigation Satellite System (GNSS)-based remote sensing method for simulating Radar Doppler Map (RDM) features through joint electromagnetic scattering modeling and signal processing, enabling characteristic parameter extraction for both point and ship targets in multi-satellite scenarios. Simulations demonstrate that the B3I signal achieves a significantly enhanced range resolution (tens of meters) compared to the B1I signal (hundreds of meters), attributable to its wider bandwidth. Furthermore, we introduce an Unscented Particle Filter (UPF) algorithm for dynamic target tracking and state estimation. Experimental results show that four-satellite configurations outperform three-satellite setups, achieving <10 m position error for uniform motion and <18 m for maneuvering targets, with velocity errors within ±2 m/s using four satellites. The joint detection framework for multi-satellite, multi-target scenarios demonstrates an improved detection accuracy and robust localization performance. Full article

Background/Objectives: The emergence of antimicrobial resistance represents a critical global health threat, requiring the discovery of novel bioactive compounds. Fungi from Amazonian biodiversity are promising sources of secondary metabolites with potential antimicrobial activity. This study aimed to investigate the production of antimicrobial compounds by two Amazonian fungal strains using the OSMAC (One Strain–Many Compounds) approach. Methods: Two fungal strains, Talaromyces pinophilus CCM-UEA-F0414 and Penicillium paxilli CCM-UEA-F0591, were cultivated under five distinct culture media to modulate secondary metabolite production. Ethyl acetate extracts were prepared and evaluated for antimicrobial activity against Gram-positive and Gram-negative bacteria, as well as pathogenic yeasts. Chemical characterization was performed using thin-layer chromatography (TLC), Fourier Transform Infrared Spectroscopy (FTIR), Ultraviolet–Visible (UV-Vis) spectroscopy, and Ultra-High-Performance Liquid Chromatography with Diode Array Detection (uHPLC-DAD). Results: The extracts exhibited significant antimicrobial activity, with minimum inhibitory concentrations (MICs) ranging from 78 to 5000 µg/mL. Chemical analyses revealed the presence of phenolic compounds, particularly caffeic and chlorogenic acids. Variations in the culture media substantially affected both the metabolite profiles and antimicrobial efficacy of the extracts. Conclusions: The OSMAC strategy effectively enhanced the metabolic diversity of the Amazonian fungal strains, leading to the production of bioactive metabolites with antimicrobial potential. These findings support the importance of optimizing culture conditions to unlock the biosynthetic capacity of Amazonian fungi as promising sources of antimicrobial agents. Full article